Tag: production data

Manufacturing Metrics that Actually Matter (The Ones We Rely On)

Part one of a multi-part series to help you measure your production efforts wisely

LNS Research blogger Mark Davidson said, “When it comes to metrics, it’s often said that what gets measured gets done.”

I have found this to be true when working with many different manufacturers. Mark also writes: “Metrics that have the attention of business and manufacturing leaders tend to be those that get measured and improved upon by their employee teams.”

I agree– measurements do drive behavior. But are employees being rewarded for metrics that do not in turn reward demand-driven flow and the customer signal (both real and imagined)?

In this set of blog posts, I want to discuss the different kinds of metrics we’re obsessed with as supply chain leaders and why the modern lean, demand-driven production manager needs to adjust or abolish some “old school” metrics altogether. But before we get into specifics, let me set up some of the environmental factors that have contributed to the current climate of “KPIs above all.”

The People’s KPIs?

Over the years, there has been a lot more attention placed upon measurements. Key Performance Indicators (KPIs) are meant to clarify how we measure what we measure and provide an underpinning for people in production to see how well they are working toward their goals.

However, the amount of responsibility and work content for most workers has grown at the same time, and left these workers with little ability to truly affect the measurements that are prevalent in today’s manufacturing environment. This erodes their ability to continue to complete the tasks that are being measured.

Even when there is a specific measurement that makes sense for the supply chain, it may not be within the individual’s ability to affect all of the measurements that they are responsible for during production. There may be contradicting measurements, and there may be cases where during one part of the month the measurement is religiously followed, while during other parts of the month, they are breaking the rules because some other measurement has become a crisis.

Count the cost

In the last 20 years, the emphasis on reducing cost has also had a profound effect on the ability of workers, supervisors and managers to focus on results. I have seen countless improvement projects implemented. In the more aggressive organizations, I have seen leaders make budgetary and staffing cuts based on the cost/benefit analysis of a project. Perhaps this isn’t so bad, but at the same time, I see little or no verification of the results and actual performance. This state of affairs has us trying to do more work with fewer people, under increased pressure with fewer results.

Metrics for Action

In the next few posts, I would like to break down the operational metrics you’ll need to empower your workforce to get results—not to just behave according to flavor-of-the-month measurements. These Metrics for Action are not intended for overall business analysis. Instead, the intent here is to cut through the clutter of the all too often, and all too many, contradicting measurements and focus on the metrics that are going to provide insight to drive action. Action to improve flow, manage constraints, direct continuous improvement efforts and more. The goal is to provide real clarity around the elements that drive organizational excellence and enhance demand-driven results.

Before we begin, here’s why we should

Assuming is the worst: Most measurements used in manufacturing are derivatives of some other objective or assumption about the nature of manufacturing. These assumptions seemed important at the time because manufacturing software and information systems didn’t support a direct link between performance and measurement. They were very important “back in the day” because they provided a framework for decision-making in a time when there were few data elements to support the decision process. This was way better than the alternative of no decisions!

Put your money where your metrics are: If you trace these measurements to cash flow, you will find some interesting conflicts. In the past, having all the relevant data for making decisions created a great deal of measurements that act as a surrogate to actual performance. These types of measurements have been around for a long time. They have become so common that they are not even considered as obsolete, but as “the way we conduct business.”

Even with today’s incredible ability to collect and contextualize data, these seemingly monolithic measurements are still being used. To test if your Manufacturing KPIs are obsolete, check to see how the measurements can be tied back into cash flow. If there is no direct link to cash in, cash out, inventory or operating expense, then your measurement may be an assumed measurement.

Customer Centric If there is no data in your company’s systems measuring what your customers are actually buying directly, then you’re working with a derivative measurement. Derivative measurements were used to simplify the planning process because the units purchased by the customer were hard to track or hard to translate into workflow. Today, synchronized, demand-driven systems can capture your customer order information across the entire production process—from order to supplier to inventory to shipment. You have all of the data points you need—but you may be still tracking derivative side-effects rather than meaningful metrics from force of habit.

The unfortunate reality is that most manufacturing measurements are the results of learned behavior, hidden behind several layers of assumptions that are obsolete or counterproductive in today’s manufacturing company. Stay with me through our metrics journey to see how you can laser-in on the metrics that really matter—to you, and to your customers.

Resources for more information:

White paper: Demand-Driven Manufacturing Metrics that Drive Action

March 12, 2018
The Magic Bullet for Real-Time Supply Chain Collaboration? Cloud Visibility.
Jessica Twentyman reported in the Financial Times, that for many manufacturers, supply chain collaboration is stuck in the dark ages. When it comes to ordering materials and components, managing inventory levels, or organizing the delivery of finished goods to customers, companies are forced continually to chase business partners – mostly suppliers, logistics companies, and retailers – via a messy stream of emails, phone calls, and even faxes. Worse still, much of the data that could give manufacturers a complete, end-to-end view of their supply chain already resides within the systems of these partners; as much as 80 percent of it, according to some industry estimates.

Supply Chain Market reported the closest any manufacturer can get to the magic bullet of efficiency (collaboration) is through greater supply chain visibility. Supply chain visibility means all partners get access to – and share data – in real-time. Visibility to all orders allows suppliers to proactively respond to demand signals. Poor visibility often results in parts shortages. Frustrated manufacturers report having no idea they were down to the last box of parts. The result is expensive; using faster shipping methods to get the part back on the shop floor. A real-time view of parts on hand allows a supply chain manager to take action before there is a stock out, eliminating expedited fees.

A single – visible – version of the truth

Modern Demand-Driven Manufacturers are leveraging real-time Cloud-based visualization and collaboration systems to view data from multiple, disparate sources while keeping the data in its original, host environment. The value of these visualization systems is in their inherent flexibility. Once the data connections are made, they can be accessed and used (with appropriate permissions) at any point along the end-to-end supply chain spectrum. There is no limit to the data sources that can be connected or how the data can be sliced and diced and made visual to accommodate the different layers and levels of the manufacturing enterprise.

The result is a single – visible – version of the truth that enables a more compliant, consistent, Lean, and waste free supply chain. Visualizations can be created or configured by and for the individual user, work center, plant or multi-plant/enterprise, supplier, or customer level. Order, replenishment status, inventory levels, machine maintenance, system alerts, KPIs, logistics tracking, and more can be made accessible to the appropriate parties anytime, anywhere, providing a single source for real-time information.

Data on Demand: Examples of value across supply chain layers
- Customers gain visibility into order receipt, status, and delivery data. In ETO environments, visibility tools can provide further collaboration capabilities on product specifications and requirements.
- Suppliers receive real-time demand signals with the ability to exchange purchase order and projected delivery information online. Supply Chain Managers can collectively visualize and track the performance of all suppliers against their service level agreements (SLAs).
- Individual users have easy access to information they can act on to analyze issues and improve performance. Customer Service representatives can follow the status of their customer’s order and confirm delivery details; Operators have a clear view of priorities and an understanding of what to work on next; Quality Analysts are immediately alerted to issues and can quickly trace the source of the problem.
- Work Centers can monitor all the machines in their area through a single screen to collectively determine overall equipment effectiveness (OEE) and gain insight for preventative or prescriptive maintenance.
- Individual Plants can visualize real-time end-to-end production flow and the status of safety, compliance, and key performance indicators (KPI) at any level in the facility.
- Regional Plant Networks can connect to Warehouse/Distribution Centers to better manage excess inventory and monitor status from Third Party Logistics (3PL) providers.
- Multi-National Enterprises can connect to global data sources – including Supplier networks and Contract Manufacturers – to assess individual plant performance and collectively view and track logistics flow throughout their enterprise.
Newer Cloud technologies are more intuitive with drag-and-drop functions and natural language queries. IT is no longer saddled with pulling data and generating reports. Through self-service tools, even non-techies can perform their own analyses and create their own dashboards and visualizations.

The technology is available and the impact of such can be far-reaching. The investment quite often produces an immediate or near-term return just in avoiding costs associated with downtime, waste and expediting.

Standardizing data formats – the key to universal, real-time accessibility.

With the multitude of data sources feeding the supply chain, the visibility value is in the ability to “mash up” or bring together data from these disparate sources to tell a complete story. The strategy for doing such is standardizing – or normalizing – data. And while this is not a new concept, today there is a more efficient and cost-effective approach. Through the Cloud, data is accessed from its host environment and aggregated, analyzed, and shared by standardizing the data and making it accessible in real-time through technology tool sets like SignalR. These lighter weight, highly flexible and scalable web-enabled technologies are rapidly replacing costly hardware devices traditionally used for data standardization.

Ultimately, visibility technologies should be measured by their ability to provide the right data to the right people at the right time. The true value proposition is in having the right information to take immediate action – the decision-driving data that will make a difference in how your supply chain is performing today.

More information on this topic:

White paper: End-to-End Supply Chain Visibility Technology is Here

Video case study: How Orbital ATK is Leveraging the IIoT and Visual Factory Technology to Drive Continuous Improvements

Video: SyncView Real-time Manufacturing Visualization System – 4 minute overview
June 19, 2017
Aligning Metrics to Strategy

Measuring your strategic goals against their value and the time, money and attention they need

When we began our metrics discussion, we talked about how behaviors are too often dictated by metrics—and whether or not these behaviors actually “move the needle” for sustainable supply chain improvements. Mark Davidson’s blog about aligning metrics to larger goals and objectives covers this topic well. I’d like to go over what I find especially valuable about these tactics. Mark writes: “Largely due to the misalignment of goals and objectives, a considerable number of organizations struggle to realize the full business value that manufacturing can generate.” (e.g., Don’t miss the boat.)

Let’s talk about the “real-world” first. We all know that in today’s organizations there are many, competing strategies and objectives. Look at any strategic plan, and there are many initiatives that cover the gambit of popular business systems, such as CRM, Big Data, Business Intelligence, Cloud Computing, ERP implementations, Supply Chain implementations, Human Resources employee engagement programs, Safety Programs, etc. There’s no shortage of cost savings and performance enhancing methods to transform organizations. Yet, without a good way to measure them, they will meet a great deal of resistance.

Who is driving this thing?

One of the biggest issues I see is that once strategic objectives are accepted, people start making assumptions. These assumptions have effects that start to come to light when the tasks and activities are disseminated and the people responsible for implementing the changes start working. These people are already busy, and now we add new tasks for them to accomplish, often overloading them. If there are multiple strategies to work on among the same teams, then there is a worse problem, as these “difference makers” compete for time, attention, and money.

Remember, someone has put their butt on the line to drive these strategic objectives. It seems we all have to have several people in leadership whose job it is to drive these objectives—and the rest of us in an organization have a conflict between the objective’s tasks and our daily workload.

Getting SMART

Savvy manufacturers set “SMART” goals—Specific, Measurable, Actionable, Realistic, Time-Based.

It’s important to understand the interrelationships between high-level goals and objectives as well as what actions or methods are required for an organization to achieve them – this falls under Specific. Measurable and Actionable are when metrics come into play—any desired result must have a set of defined measurements, targets, and actions that can be taken in order to “move the needle” on the metrics that are leading or lagging indicators of results.

If an organization is only creating one measurement to support one strategic objective, applying SMART makes sense.

Beware of too much noise

The reality is, it’s hard to limit ourselves to one measurement per objective. So, ask yourself, how many new measurements and objectives do you have? Are they all in alignment and driving the desired behavior? The pressure for too many measurements creates dysfunction within the organization. All these initiatives create competition for scarce resources and even more scarce time for change. And, we often find that when you have too many metrics, at some point they may even work against each other. The result is a contentious and noisy organization that struggles to make any sustainable improvements.

That’s why Davidson talks about not only setting KPIs but ensuring that there are processes in place to act on what they reveal. He also insists upon effective communication strategies around the KPIs as well as tying them into the organization’s performance incentives. These are solid ways to ensure that the strategies are not only assigned, but measured, and that the results you achieve really help your organization become more valuable—internally profitable and externally, to become a partner of choice to your customers.

Every day we work with manufacturers applying demand-driven methods to align all aspects of their operations in order to drive the optimal rate of production flow. This strategy is backed by a specific set of operational metrics these manufacturers measure and take action on for continuous performance improvement.

Next time- we’ll get more into specific, actionable metrics you’ll need for your demand-driven, lean manufacturing change. Many of the strategies your organization needs to initiate to get the most out of the supply chain function link to becoming more responsive to demand. We’ll figure out how to do that by measuring the right things at the right time for the right results. Read the white paper, Demand-Driven Manufacturing Metrics that Drive Action, to start thinking how you would like to align your metrics to strategy.

February 13, 2017
If it’s Not Real Time Data, It’s Old Data
We have so much real-time data around us in our daily routines. A barista starts to prepare my order the moment that I purchase my daily coffee. I instantly know how close I am to the speed limit thanks to my car’s speedometer. And I see an accurate count down of the number of minutes before my computer turns off due to a drained battery. Since all of this real-time data is available in our day-to-day lives, shouldn’t we expect the same for data we use in our manufacturing organizations?

Countless times I have walked into customer sites on Day 1 and seen old data everywhere. I have seen four walls of a conference room covered with 8 ½” by 11” printed reports, most of which were multiple weeks old. Or users that explain that they perform analysis based off of desktop spreadsheet files, with manual data loads. In each of these cases, people are operating off of old data, even if it was updated just a few hours ago. If my speedometer had that same delay, I would have a lot more speeding tickets!

Old Data is Just… Old Data

Manufacturers today are asking themselves how they can do better and be better. They realize that to be competitive, they should look inside the factory first and explore their own processes to find areas for improvement. If they analyze their data to see what it shows about their operations, they tend think that any data to go off of is better than no data, right? Not always, I say.

Based on how fast your environment changes, it could be detrimental to make decisions off of old data. Since the pace of business has increased for manufacturers, thanks to both technology and complexity, so too should the pace at which data is collected and made available to make informed decisions. For example, consider everything that can happen in the span of an hour:
- Purchasing finds out that a truck shipment of raw materials will be delayed two days due to weather.
- A new customer puts in a rush online order double the size of previous months.
- Maintenance begins fixing a problem on a constraint resource that is estimated to take at least a couple of hours.
Wouldn’t your organization want to know about all of these situations as soon as it could? Certainly. Keep in mind, however, that as more and more data is available, you’ll need to discern if, when, and how you take action. That is, you’ll need to separate knowing that events occur versus reacting to them right away. Each event could immediately impact your organization’s priorities, but you also don’t want to be jumpy and let every event disrupt your overall process. The important thing is that you are aware and that you have the right information at hand to make necessary decisions.

Better yet, your systems can also be aware of this same event data and alert you only to the issues that require your intervention. Technology solutions for manufacturers should be able to take real-time data, assess it against other conditions and values, and then notify you to respond only to the events that need your attention. This is the nature of demand-driven manufacturing – since the focus is on overall production flow, you only need to address those issues that disrupt flow. The rest is probably just normal “noise” – or what becomes a normal day for a manufacturer.

Manual Reporting Makes Data Stale

So how did we get to the point where so many manufacturers are not using real-time information? Thankfully, manufacturing technology is catching up to provide all of the information and analytics that companies seek in an automated, real-time manner. Organizations have always had the desire for information and reports, but they’ve commonly only had manual methods as options. Consider the volume of reporting that a typical manufacturing company does on a recurring basis – that’s a lot of manual reporting happening based on non-real time data. Think of the time drain that both the manual data collection and report running put on a company. If it takes an analyst only two hours to run a report, that means they are already using information that’s at least two hours old.

If you run reports on yesterday’s manually collected data, then you will only have information about yesterday. Further, we will still need a clear, straightforward way to display that information to users. I know my car’s current speed based on the easy-to-read dashboard, for example. If we demand that our organizations collect real-time data – and we have a tool like a visual factory system to display this information – then we have a powerful platform from which to understand what is happening today and what to prepare for tomorrow within operations. In the next blog, we will pick up on this topic of how to use historical data in a meaningful way, but in the meantime, send me your comments and questions.
January 14, 2016
Visual Beats Verbal

If a picture is worth a thousand words, then visualizing a factory floor says a lot for an organization. The ability to translate any environment into a visual representation is incredibly empowering and is a strong step toward evolving a manufacturer into a connected, cutting edge company. I have had the privilege of working with organizations in their journey to becoming a ‘visual factory.’ What I have learned is that the drive to become a visual factory is founded less on a technology revolution, but more a basis to communicate with users in more natural ways.

Dominant Visual Learners

I believe the manufacturing evolution toward visual factory information systems is an example of technology catching up with basic human behavior. At 65%, visual learners make up most of the population. However, you wouldn’t think this if you consider all of the written reports, emails and spreadsheets that the average company outputs. Often, this is in absence of a tool that allows users to create the same information visually. When the result is verbose and hard-to-absorb written communication, it’s no surprise that people have difficulty retaining information. When the objective is to have all people within the system on the same page and informed, it’s best to communicate according to their preferred learning method.

Pictures are a Universal Language

A significant advantage of a visual information system is its universal nature and language independence. Visual factory systems use elements such as diagrams, charts, and colored indicators to communicate status with very few words. In my experience, organizations have a wide range of language and literacy levels. User adoption increases based on the tool’s ease of use, but also by having all users comfortable with using the information that the system presents. Additionally, removing written components also makes the information more understandable across languages. This is an important feature for global enterprises.

Allow Antidotes to be Created

In a slightly contradictory way, the other advantage of a factory visualization system is that it doesn’t spell out everything for a user. In my experience, writing out what people should be learning doesn’t always lead to higher information retention. It’s good for them to create an antidote in their mind about what they see. Naturally, when someone looks at a simple, clear diagram or picture, they take a brief moment to absorb the information and come to some sort of conclusion. They are taking in the visual elements and making a judgement or asking a question based on what they see. If they have a question, ideally they interact with screen components and drill into the visualizations to learn more. Creating the antidote of what they observe leads to more user investment and sense of ownership with the tool and information. Sharing this antidote with other people also increases understanding. This is key to making a visual factory system the primary tool in a continuous improvement journey. For example, when an employee sees a downward trend in on-time delivery, perhaps they drill through to escalated maintenance information related to a resource. The maintenance information may display time series data to the employee, showing increased downtime every day around a consistent period. The employee could come to a conclusion that to improve and prevent this downtime – and avoid compromising deliveries – planned maintenance could occur weekly to make sure the utilized resource is running at its maximum available capacity.

While manufacturing companies have been creating reports for many years, only now do they have options when it comes to visual factory applications. Being able to reach users at every level in the organization and clearly communicate status is the dream for any manufacturer. The benefits of a visual factory are far superior to the verbal and written alternatives. Next time, I will explore the potential and power behind real-time visual factory metrics. Until then, feel free to send me your questions or experiences on anything visual factory related.

September 24, 2015
Three Ways Your Data Empowers Customer Confidence
The Internet of Things helps differentiate your company by providing more information and insight so you can be more agile in responding to customer needs.

I’ve spent my career in marketing explaining to people how having the right software will make them the right company for their customers. Can it really be that simple? I think it is.

When the Gartner Group first put voice to the concept of an interconnected world, one in which Cloud-based software, linking to things (products, machines, etc.) creates an “Internet of Things” that holds incredible value for customers — I nearly rose from my desk and cheered. Experts say that by 2025, this vast network will be worth over $225 billion dollars. To me that number represents value for customers who work with manufacturers who know how to harness all of zillions of bytes of data included in this network. And if you are such a manufacturer, you should be already on your way to creating your own, mini, Internet of Things across your supply chain.

Data as Differentiator

I understand that using data as a differentiator seems daunting. But please consider that in this new world, data is the single most important driver to your growth in the marketplace. The actual products you produce can no longer meet your customers’ needs by themselves. I don’t think it’s too strong of a statement to declare—your data can and will make or break your customer relationships. Here are just three ways:
1. 1. Machine-level data gives you unsurpassed control over your flow—Connecting machines to the rest of your production data allows you to truly identify the constraints to flow on the shop floor. Identifying issues with flow on the machine level creates an environment where your promise to order promises are as real as they get. And your customers will stay satisfied.
  2. Hooking up suppliers to your data network allows you control over your supplier relationships—If you don’t have your suppliers included on your own Internet of Things, you’re missing out. As you know better than anyone, your finished goods can’t get to your customer until and unless you have figured out a way to manage your inventory appropriately. Having your suppliers’ supply chains included in your digitized, inventory management software solves this problem.
  3. Controlling flow by digitizing your production process frees up capacity and allows you to meet new customer needs—You can start by using software to manage inventory. That will often give you enough new capacity to create new opportunities to meet customer needs. Once you get an entire platform connected, you will delight your customer. How? By gaining access to actionable data that lets you identify constraints in real-time and improves your time to delivery. In empowering people to act quickly to mitigate constraints, you are protecting your customers’ orders. And by creating a business environment that promotes continuous improvement, your customers see that you are truly focused on being the best you can be — for their benefit.
Of course, your own Internet of Things at your company empowers you in many more ways. I will talk about these in later posts. I think together we can uncover even more exciting trends about how software and the Internet of Things creates value for our customers. In fact, if you have any stories about how harnessing your big data has granted you big rewards, definitely send them to me. I’d love to hear from you.

– Marketing

Big data, the Internet of Things, Industry 4.0, Factory of the Future, the Visual factory – what do you really need to pay attention to and what do these concepts mean to most manufacturers? A sceptic and trend-spotter, Pam’s posts leverage a background in technology marketing to apply these big concepts to the real world – and real work – of demand-driven manufacturers.

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November 4, 2014

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